In cereals seed, the accumulation of storage compounds is tightly regulated at the transcriptiona... more In cereals seed, the accumulation of storage compounds is tightly regulated at the transcriptional level providing interesting models for the analysis of regulatory networks. This accumulation is programmed but also influenced both by nitrogen and sulfur availability. Study of the global transcriptional time and/or tissue specific programming as well as regulation arising from various nitrogen and sulfur supply levels provides valuable information toward nutritional value improvement. In this work, three distinct microarray experiments were carried out on wheat (Triticum aestivum L.) to measure the expression of 40 642 genes, including 2 891 transcription factors (TFs) in 98 conditions of time, tissue and nutrition. An extensive comparative transcriptomic analysis was thereby carried out to observe spatial and time-specific gene expression. Focus was made on TFs and an innovative network inference method was applied to highlight those implied in this regulation. It was observed that...
Modelling European Agriculture with Climate Change for Food Security (MACSUR) is a knowledge hub ... more Modelling European Agriculture with Climate Change for Food Security (MACSUR) is a knowledge hub exploiting and improving data, methods and modelling tools for a detailed climate change risk assessment. The hub comprises 73 interacting agricultural (crop, livestock, trade) scientific and modelling research groups from 16 European countries and Israel. The crop modelling (CropM) component of MACSUR concentrates on overcoming weaknesses in crop modelling approaches and tools with specific attention to exploiting data on important European field crops, crop rotations and farming systems, and the modelling of diverse (mitigative) adaptation options. CropM outputs are scaled up to farm, regional and (supra-) national level as required for concerted integrated studies on the European agri-food sector and its contribution to global food security under climate change. The specific objectives of CropM are: (i) to conduct crop model intercomparisons to detect deficiencies, (ii) compile data i...
The pressure of economic cost and environmental constraints dictates that farmers must optimize t... more The pressure of economic cost and environmental constraints dictates that farmers must optimize the use of nitrogen fertilizer. Industrial uses of new wheat varieties require specific and stable grain protein concentration, which needs accurate estimation of N demand during the crop cycle. Thus breeding for high N use efficiency (NUE) and yield, whilst maintaining high grain protein concentration, is of high priority for cereal geneticists. Here, the wheat simulation model SiriusQuality1 was used to analyse the effect of variation in physiological traits on wheat NUE, grain protein composition and concentration under variable climate and conventional and limited N supply conditions. Twenty-three of the 53 parameters of SiriusQuality1 were selected for sensitivity analysis based on a literature surveyfour parameters were related to phenology and canopy development, seven to crop C assimilation and partitioning, eight to crop N uptake and assimilation, and four to grain development and C and N accumulation. Variations in weather and N treatments induced larger variations in NUE than most of the physiological traits considered. The simulations suggest that a single physiological trait is unlikely to break the negative correlation between the grain protein concentration and yield over a wide range of sites and seasons, especially under low N input environments. Increasing the N storage capacity of the leaves and stem and the allocation of N to non-structural proteins appeared as the more promising strategy to breaking the negative correlation between grain yield and protein concentration.
Wheat (Triticum aestivum L.) grain storage proteins (GSPs) are major determinants of flour end-us... more Wheat (Triticum aestivum L.) grain storage proteins (GSPs) are major determinants of flour end-use value. Biological and molecular mechanisms underlying the developmental and nutritional determination of GSP accumulation in cereals are as yet poorly understood. Here we timed the accumulation of GSPs during wheat grain maturation relative to changes in metabolite and transcript pools in different conditions of nitrogen (N) and sulfur (S) availability. We found that the N/S supply ratio modulated the duration of accumulation of S-rich GSPs and the rate of accumulation of S-poor GSPs. These changes are likely to be the result of distinct relationships between N and S allocation, depending on the S content of the GSP. Most developmental and nutritional modifications in GSP synthesis correlated with the abundance of structural gene transcripts. Changes in the expression of transport and metabolism genes altered the concentrations of several free amino acids under variable conditions of N and S supply, and these amino acids seem to be essential in determining GSP expression. The comprehensive data set generated and analyzed here provides insights that will be useful in adapting fertilizer use to variable N and S supply, or for breeding new cultivars with balanced and robust GSP composition.
With the increasing amount of -omics data available, a particular effort has to be made to provid... more With the increasing amount of -omics data available, a particular effort has to be made to provide suitable analysis tools. A major challenge is that of unraveling the molecular regulatory networks from massive and heterogeneous datasets. Here we describe RulNet, a weboriented platform dedicated to the inference and analysis of regulatory networks from qualitative and quantitative -omics data by means of rule discovery. Queries for rule discovery can be written in an extended form of the RQL query language, which has a syntax similar to SQL. RulNet also offers users interactive features that progressively adjust and refine the inferred networks. In this paper, we present a functional characterization of RulNet and compare inferred networks with correlation-based approaches. The performance of RulNet has been evaluated using the three benchmark datasets used for the transcriptional network inference challenge DREAM5. Overall, RulNet performed as well as the best methods that participated in this challenge and it was shown to behave more consistently when compared across the three datasets. Finally, we assessed the suitability of RulNet to analyze experimental -omics data and to infer regulatory networks involved in the response to nitrogen and sulfur supply in wheat (Triticum aestivum L.) grains. The results highlight putative actors governing the response to nitrogen and sulfur supply in wheat grains. We evaluate the main characteristics and features of RulNet as an all-in-one solution for RN inference, visualization and editing. Using simple yet powerful RulNet queries allowed RNs involved in the adaptation of wheat grain to N and S supply to be discovered. We demonstrate the effectiveness and suitability of RulNet as a platform for the analysis of RNs involving different types of -omics data. The results are promising since they are consistent with what was previously established by the scientific community.
Increasing use of regionally and globally oriented impacts studies, coordinated across internatio... more Increasing use of regionally and globally oriented impacts studies, coordinated across international modelling groups, promises to bring about a new era in climate impacts research. Coordinated cycles of model improvement and projection are needed to make the most of this potential.
ICP Series on Climate Change Impacts, Adaptation, and Mitigation, 2014
ABSTRACT Many simulation studies have been carried out to predict the effect of climate change on... more ABSTRACT Many simulation studies have been carried out to predict the effect of climate change on crop yield. Typically, in such study, one or several crop models are used to simulate series of crop yield values for different climate scenarios corresponding to different hypotheses of temperature, CO2 concentration, and rainfall changes. These studies usually generate large datasets including thousands of simulated yield data. The structure of these datasets is complex because they include series of yield values obtained with different mechanistic crop models for different climate scenarios defined from several climatic variables (temperature, CO2 etc.). Statistical methods can play a big part for analyzing large simulated crop yield datasets, especially when yields are simulated using an ensemble of crop models. A formal statistical analysis is then needed in order to estimate the effects of different climatic variables on yield, and to describe the variability of these effects across crop models. Statistical methods are also useful to develop meta-models i.e., statistical models summarizing complex mechanistic models. The objective of this paper is to present a random-coefficient statistical model (mixed-effects model) for analyzing large simulated crop yield datasets produced by the international project AgMip for several major crops. The proposed statistical model shows several interesting features; i) it can be used to estimate the effects of several climate variables on yield using crop model simulations, ii) it quantities the variability of the estimated climate change effects across crop models, ii) it quantifies the between-year yield variability, iv) it can be used as a meta-model in order to estimate effects of new climate change scenarios without running again the mechanistic crop models. The statistical model is first presented in details, and its value is then illustrated in a case study where the effects of climate change scenarios on different crops are compared.
Improving crop performance to satisfy an increasing demand for agricultural products is a constan... more Improving crop performance to satisfy an increasing demand for agricultural products is a constant challenge to plant scientists. The recent improvements of process-based simulation models offer new avenues to explore variations of genetic traits on crop performance. In this study, global sensitivity analyses were performed using the Morris and Sobol' methods sequentially to identify influential parameters of the SiriusQuality1 wheat simulation model. Twenty three influential parameters were identified. The response of the model outputs to these parameters was analyzed. A genetic algorithm with self-adaptation was then developed to optimize these parameters for 16 genotypes of wheat and to define the minimum set of parameters needed to simulate genetic differences in grain yield under diverse environments.
Increasing attention is being devoted to root system architecture in drought tolerance studies an... more Increasing attention is being devoted to root system architecture in drought tolerance studies and breeding. Surprisingly, while the explicit consideration of architecture is a key to system-wide approaches of water dynamics in the soil-plant continuum, plant biologists often take soil water distribution as an external given, which leads to such expectations that deep roots warrant improved access to soil water resources. This view may underemphasize the influence of root architecture on soil moisture and nutrient distributions at the macroscopic to the plant scales. In addition, although the impact of onedimensional root distributions on the profile of depletion of soil water content has been shown in numerous studies, horizontal water content variability may arise due to contrasting uptake by different root segments and redistribution processes, even with uniform horizontal soil hydraulic properties. In this paper, we highlight the importance of addressing the dynamics of the soil matrix in plant biology, to understand how water fluxes driven by soil and plant processes affect water availability and uptake throughout a growth cycle. From early modeling efforts focusing on one-dimensional effective root water uptake, two-and three-dimensional models that involve a higher level of complexity in the description of root structure and related soil and plant processes are now being developed. We anticipate that coupling such water dynamics models with QTL-based structure-function plant models will better allow the integration of environmental and genetic constraints to support model-assisted design of plant architectures susceptible to improve yield under given drought scenarios.
Nitrogen (N) nutrition, post-anthesis temperature and drought-induced changes in the kinetics of ... more Nitrogen (N) nutrition, post-anthesis temperature and drought-induced changes in the kinetics of accumulation of dry mass, total grain N and protein fractions (albumins-globulins, amphiphils, gliadins, and glutenins) contents were examined for winter wheat (Triticum aestivum L.). Crops were grown in controlled environment tunnels in 1994 and 1998. In 1994, ®ve post-anthesis temperatures averaging from 15±25°C were applied during grain-®lling. In 1998 two post-anthesis temperatures averaging 13°C and 20°C were applied and factorized with two postanthesis water regimes. In 1994 crops also were grown in the ®eld, where different application rates and timing of N nutrition were tested. When expressed in thermal time, the kinetics of accumulation of the protein fractions were not signi®cantly affected by post-anthesis temperature or drought; whereas N nutrition signi®cantly increased the rate and duration of accumulation of storage proteins. Albumin-globulin proteins accumulated during the early stage of grain development. The rate of accumulation of that fraction decreased signi®cantly at c. 250°Cd after anthesis, when the storage proteins (gliadins and glutenins) started to accumulate signi®cantly. Single allometric relationships for the different environmental conditions exist between the quantity of each protein fraction and the total quantity of N per grain. From these results it was concluded that (1) the process of N partitioning is neither signi®cantly affected by post-anthesis temperature or drought nor by the rate and timing of N nutrition and (2) at maturity, variations in protein fraction composition are mainly because of differences in the total quantity of N accumulated during grain-®lling.
In cereals seed, the accumulation of storage compounds is tightly regulated at the transcriptiona... more In cereals seed, the accumulation of storage compounds is tightly regulated at the transcriptional level providing interesting models for the analysis of regulatory networks. This accumulation is programmed but also influenced both by nitrogen and sulfur availability. Study of the global transcriptional time and/or tissue specific programming as well as regulation arising from various nitrogen and sulfur supply levels provides valuable information toward nutritional value improvement. In this work, three distinct microarray experiments were carried out on wheat (Triticum aestivum L.) to measure the expression of 40 642 genes, including 2 891 transcription factors (TFs) in 98 conditions of time, tissue and nutrition. An extensive comparative transcriptomic analysis was thereby carried out to observe spatial and time-specific gene expression. Focus was made on TFs and an innovative network inference method was applied to highlight those implied in this regulation. It was observed that...
Modelling European Agriculture with Climate Change for Food Security (MACSUR) is a knowledge hub ... more Modelling European Agriculture with Climate Change for Food Security (MACSUR) is a knowledge hub exploiting and improving data, methods and modelling tools for a detailed climate change risk assessment. The hub comprises 73 interacting agricultural (crop, livestock, trade) scientific and modelling research groups from 16 European countries and Israel. The crop modelling (CropM) component of MACSUR concentrates on overcoming weaknesses in crop modelling approaches and tools with specific attention to exploiting data on important European field crops, crop rotations and farming systems, and the modelling of diverse (mitigative) adaptation options. CropM outputs are scaled up to farm, regional and (supra-) national level as required for concerted integrated studies on the European agri-food sector and its contribution to global food security under climate change. The specific objectives of CropM are: (i) to conduct crop model intercomparisons to detect deficiencies, (ii) compile data i...
The pressure of economic cost and environmental constraints dictates that farmers must optimize t... more The pressure of economic cost and environmental constraints dictates that farmers must optimize the use of nitrogen fertilizer. Industrial uses of new wheat varieties require specific and stable grain protein concentration, which needs accurate estimation of N demand during the crop cycle. Thus breeding for high N use efficiency (NUE) and yield, whilst maintaining high grain protein concentration, is of high priority for cereal geneticists. Here, the wheat simulation model SiriusQuality1 was used to analyse the effect of variation in physiological traits on wheat NUE, grain protein composition and concentration under variable climate and conventional and limited N supply conditions. Twenty-three of the 53 parameters of SiriusQuality1 were selected for sensitivity analysis based on a literature surveyfour parameters were related to phenology and canopy development, seven to crop C assimilation and partitioning, eight to crop N uptake and assimilation, and four to grain development and C and N accumulation. Variations in weather and N treatments induced larger variations in NUE than most of the physiological traits considered. The simulations suggest that a single physiological trait is unlikely to break the negative correlation between the grain protein concentration and yield over a wide range of sites and seasons, especially under low N input environments. Increasing the N storage capacity of the leaves and stem and the allocation of N to non-structural proteins appeared as the more promising strategy to breaking the negative correlation between grain yield and protein concentration.
Wheat (Triticum aestivum L.) grain storage proteins (GSPs) are major determinants of flour end-us... more Wheat (Triticum aestivum L.) grain storage proteins (GSPs) are major determinants of flour end-use value. Biological and molecular mechanisms underlying the developmental and nutritional determination of GSP accumulation in cereals are as yet poorly understood. Here we timed the accumulation of GSPs during wheat grain maturation relative to changes in metabolite and transcript pools in different conditions of nitrogen (N) and sulfur (S) availability. We found that the N/S supply ratio modulated the duration of accumulation of S-rich GSPs and the rate of accumulation of S-poor GSPs. These changes are likely to be the result of distinct relationships between N and S allocation, depending on the S content of the GSP. Most developmental and nutritional modifications in GSP synthesis correlated with the abundance of structural gene transcripts. Changes in the expression of transport and metabolism genes altered the concentrations of several free amino acids under variable conditions of N and S supply, and these amino acids seem to be essential in determining GSP expression. The comprehensive data set generated and analyzed here provides insights that will be useful in adapting fertilizer use to variable N and S supply, or for breeding new cultivars with balanced and robust GSP composition.
With the increasing amount of -omics data available, a particular effort has to be made to provid... more With the increasing amount of -omics data available, a particular effort has to be made to provide suitable analysis tools. A major challenge is that of unraveling the molecular regulatory networks from massive and heterogeneous datasets. Here we describe RulNet, a weboriented platform dedicated to the inference and analysis of regulatory networks from qualitative and quantitative -omics data by means of rule discovery. Queries for rule discovery can be written in an extended form of the RQL query language, which has a syntax similar to SQL. RulNet also offers users interactive features that progressively adjust and refine the inferred networks. In this paper, we present a functional characterization of RulNet and compare inferred networks with correlation-based approaches. The performance of RulNet has been evaluated using the three benchmark datasets used for the transcriptional network inference challenge DREAM5. Overall, RulNet performed as well as the best methods that participated in this challenge and it was shown to behave more consistently when compared across the three datasets. Finally, we assessed the suitability of RulNet to analyze experimental -omics data and to infer regulatory networks involved in the response to nitrogen and sulfur supply in wheat (Triticum aestivum L.) grains. The results highlight putative actors governing the response to nitrogen and sulfur supply in wheat grains. We evaluate the main characteristics and features of RulNet as an all-in-one solution for RN inference, visualization and editing. Using simple yet powerful RulNet queries allowed RNs involved in the adaptation of wheat grain to N and S supply to be discovered. We demonstrate the effectiveness and suitability of RulNet as a platform for the analysis of RNs involving different types of -omics data. The results are promising since they are consistent with what was previously established by the scientific community.
Increasing use of regionally and globally oriented impacts studies, coordinated across internatio... more Increasing use of regionally and globally oriented impacts studies, coordinated across international modelling groups, promises to bring about a new era in climate impacts research. Coordinated cycles of model improvement and projection are needed to make the most of this potential.
ICP Series on Climate Change Impacts, Adaptation, and Mitigation, 2014
ABSTRACT Many simulation studies have been carried out to predict the effect of climate change on... more ABSTRACT Many simulation studies have been carried out to predict the effect of climate change on crop yield. Typically, in such study, one or several crop models are used to simulate series of crop yield values for different climate scenarios corresponding to different hypotheses of temperature, CO2 concentration, and rainfall changes. These studies usually generate large datasets including thousands of simulated yield data. The structure of these datasets is complex because they include series of yield values obtained with different mechanistic crop models for different climate scenarios defined from several climatic variables (temperature, CO2 etc.). Statistical methods can play a big part for analyzing large simulated crop yield datasets, especially when yields are simulated using an ensemble of crop models. A formal statistical analysis is then needed in order to estimate the effects of different climatic variables on yield, and to describe the variability of these effects across crop models. Statistical methods are also useful to develop meta-models i.e., statistical models summarizing complex mechanistic models. The objective of this paper is to present a random-coefficient statistical model (mixed-effects model) for analyzing large simulated crop yield datasets produced by the international project AgMip for several major crops. The proposed statistical model shows several interesting features; i) it can be used to estimate the effects of several climate variables on yield using crop model simulations, ii) it quantities the variability of the estimated climate change effects across crop models, ii) it quantifies the between-year yield variability, iv) it can be used as a meta-model in order to estimate effects of new climate change scenarios without running again the mechanistic crop models. The statistical model is first presented in details, and its value is then illustrated in a case study where the effects of climate change scenarios on different crops are compared.
Improving crop performance to satisfy an increasing demand for agricultural products is a constan... more Improving crop performance to satisfy an increasing demand for agricultural products is a constant challenge to plant scientists. The recent improvements of process-based simulation models offer new avenues to explore variations of genetic traits on crop performance. In this study, global sensitivity analyses were performed using the Morris and Sobol' methods sequentially to identify influential parameters of the SiriusQuality1 wheat simulation model. Twenty three influential parameters were identified. The response of the model outputs to these parameters was analyzed. A genetic algorithm with self-adaptation was then developed to optimize these parameters for 16 genotypes of wheat and to define the minimum set of parameters needed to simulate genetic differences in grain yield under diverse environments.
Increasing attention is being devoted to root system architecture in drought tolerance studies an... more Increasing attention is being devoted to root system architecture in drought tolerance studies and breeding. Surprisingly, while the explicit consideration of architecture is a key to system-wide approaches of water dynamics in the soil-plant continuum, plant biologists often take soil water distribution as an external given, which leads to such expectations that deep roots warrant improved access to soil water resources. This view may underemphasize the influence of root architecture on soil moisture and nutrient distributions at the macroscopic to the plant scales. In addition, although the impact of onedimensional root distributions on the profile of depletion of soil water content has been shown in numerous studies, horizontal water content variability may arise due to contrasting uptake by different root segments and redistribution processes, even with uniform horizontal soil hydraulic properties. In this paper, we highlight the importance of addressing the dynamics of the soil matrix in plant biology, to understand how water fluxes driven by soil and plant processes affect water availability and uptake throughout a growth cycle. From early modeling efforts focusing on one-dimensional effective root water uptake, two-and three-dimensional models that involve a higher level of complexity in the description of root structure and related soil and plant processes are now being developed. We anticipate that coupling such water dynamics models with QTL-based structure-function plant models will better allow the integration of environmental and genetic constraints to support model-assisted design of plant architectures susceptible to improve yield under given drought scenarios.
Nitrogen (N) nutrition, post-anthesis temperature and drought-induced changes in the kinetics of ... more Nitrogen (N) nutrition, post-anthesis temperature and drought-induced changes in the kinetics of accumulation of dry mass, total grain N and protein fractions (albumins-globulins, amphiphils, gliadins, and glutenins) contents were examined for winter wheat (Triticum aestivum L.). Crops were grown in controlled environment tunnels in 1994 and 1998. In 1994, ®ve post-anthesis temperatures averaging from 15±25°C were applied during grain-®lling. In 1998 two post-anthesis temperatures averaging 13°C and 20°C were applied and factorized with two postanthesis water regimes. In 1994 crops also were grown in the ®eld, where different application rates and timing of N nutrition were tested. When expressed in thermal time, the kinetics of accumulation of the protein fractions were not signi®cantly affected by post-anthesis temperature or drought; whereas N nutrition signi®cantly increased the rate and duration of accumulation of storage proteins. Albumin-globulin proteins accumulated during the early stage of grain development. The rate of accumulation of that fraction decreased signi®cantly at c. 250°Cd after anthesis, when the storage proteins (gliadins and glutenins) started to accumulate signi®cantly. Single allometric relationships for the different environmental conditions exist between the quantity of each protein fraction and the total quantity of N per grain. From these results it was concluded that (1) the process of N partitioning is neither signi®cantly affected by post-anthesis temperature or drought nor by the rate and timing of N nutrition and (2) at maturity, variations in protein fraction composition are mainly because of differences in the total quantity of N accumulated during grain-®lling.
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Papers by Pierre Martre